Introduction to Operations Research, Volume 1CD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 157
... sensitivity analysis of c1 and C2 for the Wyndor Glass Co. problem . Starting with the original objective function line [ where c1 = 3 , c2 = 5 , C1 and the optimal solution is ( 2 , 6 ) ] , the other two lines show the extremes of how ...
... sensitivity analysis of c1 and C2 for the Wyndor Glass Co. problem . Starting with the original objective function line [ where c1 = 3 , c2 = 5 , C1 and the optimal solution is ( 2 , 6 ) ] , the other two lines show the extremes of how ...
Page 254
... sensitivity analysis on the coefficients of the new variable added to the primal problem . By simply checking the new dual constraint , you can immediately see how far any of these ... SENSITIVITY ANALYSIS The Essence of Sensitivity Analysis.
... sensitivity analysis on the coefficients of the new variable added to the primal problem . By simply checking the new dual constraint , you can immediately see how far any of these ... SENSITIVITY ANALYSIS The Essence of Sensitivity Analysis.
Page 262
... small changes that do not affect the feasibility of the current basic so- lution ( and so do not affect the y * values ) . Consequently , the OR team has investigated the marginal profitability 262 6 DUALITY THEORY AND SENSITIVITY ANALYSIS.
... small changes that do not affect the feasibility of the current basic so- lution ( and so do not affect the y * values ) . Consequently , the OR team has investigated the marginal profitability 262 6 DUALITY THEORY AND SENSITIVITY ANALYSIS.
Other editions - View all
Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost CPF solution CPLEX decision variables described dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphical identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero